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Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes

Nature 2022年第7909期605卷 E3页

作者： Jill E Moore Michael J Purcaro Henry E Pratt Charles B Epstein Noam Shoresh Jessika Adrian Trupti Kawli Carrie A Davis Alexander Dobin Rajinder Kaul Jessica Halow Eric L Van Nostrand Peter Freese David U Gorkin Yin Shen Yupeng He Mark Mackiewicz Florencia Pauli-Behn Brian A Williams Ali Mortazavi Cheryl A Keller Xiao-Ou Zhang Shaimae I Elhajjajy Jack Huey Diane E Dickel Valentina Snetkova Xintao Wei Xiaofeng Wang Juan Carlos Rivera-Mulia Joel Rozowsky Jing Zhang Surya B Chhetri Jialing Zhang Alec Victorsen Kevin P White Axel Visel Gene W Yeo Christopher B Burge Eric Lécuyer David M Gilbert Job Dekker John Rinn Eric M Mendenhall Joseph R Ecker Manolis Kellis Robert J Klein William S Noble Anshul Kundaje Roderic Guigó Peggy J Farnham J Michael Cherry Richard M Myers Bing Ren Brenton R Graveley Mark B Gerstein Len A Pennacchio Michael P Snyder Bradley E Bernstein Barbara Wold Ross C Hardison Thomas R Gingeras John A Stamatoyannopoulos Zhiping Weng University of Massachusetts Medical School Program in Bioinformatics and Integrative Biology Worcester MA USA. The Broad Institute of Harvard and MIT Cambridge MA USA. Department of Genetics School of Medicine Stanford University Palo Alto CA USA. Cold Spring Harbor Laboratory Functional Genomics Cold Spring Harbor NY USA. Altius Institute for Biomedical Sciences Seattle WA USA. Department of Medicine University of Washington School of Medicine Seattle WA USA. Department of Cellular and Molecular Medicine Institute for Genomic Medicine Stem Cell Program Sanford Consortium for Regenerative Medicine University of California San Diego La Jolla CA USA. Program in Computational and Systems Biology Massachusetts Institute of Technology Cambridge MA USA. Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA. Ludwig Institute for Cancer Research University of California San Diego La Jolla CA USA. Institute for Human Genetics Department of Neurology University of California San Francisco San Francisco CA USA. Genomics Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA. HudsonAlpha Institute for Biotechnology Huntsville AL USA. Division of Biology and Biological Engineering California Institute of Technology Pasadena CA USA. Department of Developmental and Cell Biology University of California Irvine Irvine CA USA. Department of Biochemistry and Molecular Biology The Pennsylvania State University University Park PA USA. Environmental Genomics and Systems Biology Division Lawrence Berkeley National Laboratory Berkeley CA USA. Department of Genetics and Genome Sciences Institute for Systems Genomics UConn Health Farmington CT USA. Département de Biochimie et Médecine Moléculaire Université de Montréal Montréal Quebec Canada. Division of Experimental Medicine McGill University Montreal Quebec Canada. Institut de Recherches Cliniques de Montréal (IR

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Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas Program

arXiv

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arXiv 2019年

作者： Snyder, Michael P. Lin, Shin Posgai, Amanda Atkinson, Mark Regev, Aviv Rood, Jennifer Rozenblatt-Rosen, Orit Gaffney, Leslie Hupalowska, Anna Satija, Rahul Gehlenborg, Nils Shendure, Jay Laskin, Julia Harbury, Pehr Nystrom, Nicholas A. Bar-Joseph, Ziv Zhang, Kun Börner, Katy Lin, Yiing Conroy, Richard Procaccini, Dena Roy, Ananda L. Pillai, Ajay Brown, Marishka Galis, Zorina S. Cai, Long Shendure, Jay Trapnell, Cole Lin, Shin Jackson, Dana Snyder, Michael P. Nolan, Garry Greenleaf, William James Lin, Yiing Plevritis, Sylvia Ahadi, Sara Lee, Hayan Nevins, Stephanie Esplin, Ed Horning, Aaron Bahmani, Amir Zhang, Kun Sun, Xin Jain, Sanjay Hagood, James Kharchenko, Peter Atkinson, Mark Bodenmiller, Bernd Brusko, Todd Clare-Salzler, Michael Nick, Harry Otto, Kevin Posgai, Amanda Wasserfall, Clive Maffioletti, Sergio Caprioli, Richard M. Spraggins, Jeffrey M. Gutierrez, Danielle Patterson, Nathan Heath Neumann, Elizabeth K. Harris, Raymond deCaestecker, Mark de Plas, Raf Van Lau, Ken Cai, Long Yuan, Guo-Cheng Zhu, Qian Dries, Ruben Yin, Peng Saka, Sinem K. Kishi, Jocelyn Y. Wang, Yu Goldaracena, Isabel Laskin, Julia Ye, DongHye Burnum-Johnson, Kristin E. Piehowski, Paul D. Ansong, Charles Zhu, Ying Harbury, Pehr Desai, Tushar Mulye, Jay Chou, Peter Nagendran, Monica Bar-Joseph, Ziv Teichmann, Sarah A. Paten, Benedict Murphy, Robert F. Ma, Jian Kiselev, Vladimir Yu Kingsford, Carl Ricarte, Allyson Ruffalo, Matthew Gehlenborg, Nils Kharchenko, Peter Vella, Margaret McCallum, Chuck Börner, Katy Cross, Leonard E. Friedman, Samuel H. Heiland, Randy Herr, Bruce Macklin, Paul Quardokus, Ellen M. Record, Lisel Sluka, James P. Weber, Griffin M. Nystrom, Nicholas A. Silverstein, Jonathan C. Blood, Philip D. Ropelewski, Alexander J. Shirey, William E. Mabee, Paula Lenhardt, W. Christopher Robasky, Kimberly Michailidis, Stavros Satija, Rahul Marioni, John Regev, Aviv Butler, Andrew Stuart, Tim Fisher, Eyal Ghazanfar, Shila Rood, Jennifer Gaffney, Leslie Ersalan, Gokcen Biancalani, Tommaso Conroy, Richard Procaccini, Dena Roy, Anan School of Medicine Stanford University 300 Pasteur Drive United States Department of Genetics Stanford School of Medicine StanfordCA94305 United States Department of Medicine University of Washington SeattleWA98195 United States Department of Pathology University of Florida Diabetes Institute GainesvilleFL32610 United States Klarman Cell Observatory Broad Institute of MIT and Harvard CambridgeMA02142 United States Howard Hughes Medical Institute Koch Institute of Integrative Cancer Research Department of Biology Massachusetts Institute of Technology CambridgeMA02140 United States New York Genome Center New York CityNY10013 United States New York University New YorkNY10012 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Chemistry Purdue University West LafayetteIN47907 United States Department of Biochemistry Stanford University School of Medicine StanfordCA94305 United States Pittsburgh Supercomputing Center Carnegie Mellon University PittsburghPA15213 United States Department of Computational Biology School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Bioengineering University of California San Diego La JollaCA92093 United States Department of Intelligent Systems Engineering School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Surgery Washington University School of Medicine St LouisMO63110 United States Division of Program Coordination Planning and Strategic Initiatives National Institutes of Health BethesdaMD20892 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Caltech-UW TMC Departmen

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

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Enterotypes in the landscape of gut microbial community composition (vol 3, pg 8, 2017)

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NATURE MICROBIOLOGY 2018年第3期3卷 388-388页

作者： Costea, Paul I. Hildebrand, Falk Arumugam, Manimozhiyan Backhed, Fredrik Blaser, Martin J. Bushman, Frederic D. de Vos, Willem M. Ehrlich, S. Dusko Fraser, Claire M. Hattori, Masahira Huttenhower, Curtis Jeffery, Ian B. Knights, Dan Lewis, James D. Ley, Ruth E. Ochman, Howard O'Toole, Paul W. Quince, Christopher Relman, David A. Shanahan, Fergus Sunagawa, Shinichi Wang, Jun Weinstock, George M. Wu, Gary D. Zeller, Georg Zhao, Liping Raes, Jeroen Knight, Rob Bork, Peer European Molecular Biology Laboratory Heidelberg Germany. VIB Center for Microbiology VIB Belgium. Laboratory of Microbiology Vrije Universiteit Brussel Brussels Belgium. The Novo Nordisk Foundation Center for Basic Metabolic Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark. Wallenberg Laboratory Department of Molecular and Clinical Medicine Institute of Medicine Sahlgrenska Academy University of Gothenburg Gothenburg Sweden. Novo Nordisk Foundation Center for Basic Metabolic Research Section for Metabolic Receptology and Enteroendocrinology Faculty of Health Sciences University of Copenhagen Copenhagen Denmark. New York University Langone Medical Center New York NY USA. Department of Microbiology Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA. RPU Immunobiology Department of Bacteriology & Immunology University of Helsinki Helsinki Finland. Laboratory of Microbiology Wageningen University Wageningen The Netherlands. Metagenopolis Institut National de la Recherche Agronomique Jouy en Josas France. King's College London Centre for Host-Microbiome Interactions Dental Institute Central Office Guy's Hospital London UK. Institute for Genome Sciences at the University of Maryland School of Medicine Baltimore MD USA. Graduate School of Advanced Science and Engineering Waseda University Tokyo Japan. Department of Biostatistics Harvard School of Public Health Boston MA USA. APC Microbiome Institute University College Cork Cork Ireland. Biotechnology Institute University of Minnesota Saint Paul MN USA. Department of Computer Science and Engineering University of Minnesota Minneapolis MN USA. Center for Clinical Epidemiology and Biostatistics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. MPI Department of Microbiome Science Tübingen Germany. Department of Integrative Biology University of Texas Austin TX USA. Warwick Medical School University

Population stratification is a useful approach for a better understanding of complex biological problems in human health and wellbeing. The proposal that such stratification applies to the human gut microbiome, in the form of distinct community composition types termed enterotypes, has been met with both excitement and controversy. In view of accumulated data and re-analyses since the original work, we revisit the concept of enterotypes, discuss different methods of dividing up the landscape of possible microbiome configurations, and put these concepts into functional, ecological and medical contexts. As enterotypes are of use in describing the gut microbial community landscape and may become relevant in clinical practice, we aim to reconcile differing views and encourage a balanced application of the concept.

关键词： Community composition landscapes

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROscience 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Radiation of two small impulse current radiators

Radiation of two small impulse current radiators

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International Conference on Ultrawideband and Ultrashort Impulse Signals, UWBUSIS

作者： O.M. Dumin V.A. Plakhtii V.A. Katrich O.O. Dumina I.S. Volvach School of Radio Physics Biomedical Electronics and Computer Systems V.N. Karazin Kharkiv National University Kharkiv Ukraine Department of Higher Mathematics Ukrainian State University of Railway Transport Kharkiv Ukraine Material Science & Engineering Department University of California San Diego (UCSD) La Jolla USA

The problem of transient radiation of two small impulse current radiators is solved by vector potential method in time domain. The result is compared with the same problem for the single radiator. It is considered the classical solution for transient dipole and improved one obtained by more strict expansion for vector potential in time domain.

关键词： Transient analysis Ultra wideband technology Dipole antennas Cable shielding Electromagnetic compatibility Antenna theory Time-domain analysis

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Toward Non-Hair-Bearing Brain-computer Interfaces for Neurocognitive Lapse Detection

Toward Non-Hair-Bearing Brain-Computer Interfaces for Neuroc...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Chun-Shu Wei Yu-Te Wang Chin-Teng Lin Tzyy-Ping Jung the Swartz Center of Computational Neuroscience (SCCN) Center for Advanced Neurological Engineering (CANE) and Department of Bioengineering University of California San Diego (UCSD) La Jolla CA USA SCCN CANE and the Department of Computer Science and Engineering UCSD La Jolla CA USA the Brain Research Center and the Department of Electrical Engineering National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781424492695

Recent advances in mobile electroencephalogram (EEG) acquisition based on dry electrodes have started moving Brain-computer Interface (BCI) applications from well-controlled laboratory settings to real-world environments. However, the application mechanisms and high impedance of dry electrodes over the hair-covered areas remain challenging for everyday use of BCI. In addition, whole-scalp recordings are not always necessary or applicable due to various practical constrains. Therefore, alternative montages for EEG recordings to meet the everyday needs are in-demand. Inspired by our previous work on measuring non-hair-bearing steady state visual evoked potentials for BCI applications, this study explores the feasibility and efficacy of detecting cognitive lapses of participants based on EEG signals collected from the non-hair-bearing areas. Study results suggest that informative EEG features associated with lapses could be assessed from non-hair-bearing areas with comparable accuracy obtained from the whole-scalp EEG. The design principles, validation processes and promising findings reported in this study may enable and/or facilitate numerous BCI applications in real-world environments.

关键词： EEG BCI non-hair-bearing areas

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Lower bounds for the Gibbs sampler over mixtures of Gaussians 31

Lower bounds for the Gibbs sampler over mixtures of Gaussian...

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31st International Conference on Machine Learning, ICML 2014

作者： Tosh, Christopher Dasgupta, Sanjoy Department of Computer Science and Engineering UCSD 9500 Gilman Drive San DiegoCA92093-0404 United States

ISBN: (纸本)9781634393973

The mixing time of a Markov chain is the minimum time t necessary for the total variation distance between the distribution of the Markov chain's current state Xt and its stationary distribution to fall below some Ε > 0. In this paper, we present lower bounds for the mixing time of the Gibbs sampler over Gaussian mixture models with Dirichlet priors. Copyright © (2014) by the International Machine Learning Society (IMLS) All rights reserved.

关键词： Markov processes

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Erratum to: Weakly supervised learning of biomedical information extraction from curated data

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BMC bioinformatics 2016年第1期17卷 84页

作者： Suvir Jain Kashyap R Tumkur Tsung-Ting Kuo Shitij Bhargava Gordon Lin Chun-Nan Hsu Department of Computer Science and Engineering Jacobs School of Engineering University of California 9500 Gilman Drive La Jolla San Diego 92093 USA. Department of Biomedical Informatics School of Medicine University of California 9500 Gilman Drive La Jolla San Diego 92093 USA. Department of Biomedical Informatics School of Medicine University of California 9500 Gilman Drive La Jolla San Diego 92093 USA. chunnan@ucsd.edu.

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Single-trial identification of failed memory retrieval

Single-trial identification of failed memory retrieval

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Asilomar Conference on Signals, Systems & computers

作者： Eunho Noh Matthew V. Mollison Tim Curran Virginia R. de Sa Department of Electrical & Computer Engineering UCSD Department of Psychology and Neuroscienee Universiry of Colorado Boulder Faculty of Psychology and Neuroscience University of Colorado Boulder Faculty of Cognitive Science UCSD

We show that it is possible to distinguish unsuccessful from successful retrieval of study items based on single-trial EEG recorded during the test phase of 3 separate recognition memory experiments. The overall classification accuracy across all 34 classification problems was 58.4 %. The classification accuracy monotonically increased to 68.03 % by only classifying trials with high classifier confidence levels. The likelihood of remembering a study item for trials with the 10% highest and lowest classifier outputs were 0.80 and 0.45 respectively. This suggests that the classifier outputs are reflecting the level of retrieval during the test phase. These findings combined with previous single-trial results predicting subsequent memory from EEG recorded during and prior to memory encoding will provide a basis for a passive brain-computer interface (BCI) system for improving memory.

关键词： Accuracy Electroencephalography Brain Image color analysis Encoding Memory management Image coding

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